Interpret the coefficient on shall in regression

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Some U.S. states have enacted laws that allow citizens to carry concealed weapons. These laws are known as "shall-issue" laws because they instruct local authorities to issue a concealed weapons permit to all applicants who are citizens, are mentally competent, and have not been convicted of a felony (some states have some additional restrictions). Proponents argue that if more people carry concealed weapons, crime will decline because criminals are deterred from attacking other people. Opponents argue that crime will increase because of accidental or spontaneous use of the weapon. In this exercise, you will analyze the effect of concealed weapons laws on violent crimes. On the textbook Web site www.pearsonhighered.com/stock_watson you will find a data file Guns that contains a balanced panel of data from 50 U.S. states plus the District of Columbia for the years 1977 through 1999.3 A detailed description is given in Guns_Description, available on the Web site.

a. Estimate (1) a regression of ln(vio) against shall and (2) a regression of ln(vio) against shall, incarc_rate, density, avginc,pop,pb1064, pw1064, and pm1029.

i. Interpret the coefficient on shall in regression (2). Is this estimate large or small in a "real-world" sense?

ii. Does adding the control variables in regression (2) change the estimated effect of a shall-carry law in regression (1) as measured by statistical significance? As measured by the "real-world" significance of the estimated coefficient?

iii. Suggest a variable that varies across states but plausibly varies little-or not at all-over time and that could cause omitted variable bias in regression

Reference no: EM132855023

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